List of Articles E-Learni

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  1 - Proposing a Model for Extracting Information from Textual Documents, Based on Text Mining in E-learning
  Somayeh Ahari
  As computer networks become the backbones of science and economy, enormous quantities documents become available. So, for extracting useful information from textual data, text mining techniques have been used. Text Mining has become an important research area that disco More

  As computer networks become the backbones of science and economy, enormous quantities documents become available. So, for extracting useful information from textual data, text mining techniques have been used. Text Mining has become an important research area that discoveries unknown information, facts or new hypotheses by automatically extracting information from different written documents. Text mining aims at disclosing the concealed information by means of methods which on the one hand are able to cope with the large number of words and structures in natural language and on the other hand allow handling vagueness, uncertainty and fuzziness. Text mining, referred to as text data mining, roughly equivalent to text analytics, refers to the process of deriving high-quality information from text that high-quality information is typically derived through the patterns and processes. Moreover, text mining, also known as text data mining or knowledge discovery from textual databases, refers to the process of extracting patterns or knowledge from text documents. In this research, a survey of text mining techniques and applications in e-learning has been presented. During these studies, relevant researches in the field of e-learning were classified. After classification of researches, related problems and solutions were extracted. In this paper, first, definition of text mining is presented. Then, the process of text mining and its applications in e-learning domain are described. Furthermore, text mining techniques are introduced, and each of these methods in the field of e-learning is considered. Finally, a model for the information extraction by text mining techniques in e-learning domain is proposed. Manuscript profile
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  2 - Relation of emotional intelligence and trends of e-learning in organizations (Case study: Bank employees Alborz Province)
  Somayeh Ahari
  Today the world is moving toward a virtual space. Whereas the business, health, education, and many of the other activities would devote time and money in the past, by appearing the virtual space most of them have suitable function today. Educating is an inseparable par More

  Today the world is moving toward a virtual space. Whereas the business, health, education, and many of the other activities would devote time and money in the past, by appearing the virtual space most of them have suitable function today. Educating is an inseparable part of human which is entered to electronic world as individuals and organizations are gradually moving towards this type of educating. In this research, the relationship between emotional intelligence and trends of e-learning in organizations has been studied. The purpose of this study is applied and the research method is descriptive- survey. The questionnaire method was used to collect data. The Cronbach’s Alpha coefficient of the first questionnaire was obtained 0.76 and the second questionnaire was 0.83 which confirm the validity of the questionnaires. The content validity to test questions was used and for this purpose, experts, academics and experts were used. The population of this research is all the Alborz Province Bank Employees which 80 individuals were selected as sample size and sampling is done randomly. To analyze data the Spearman correlation coefficient and multiple regression was used. Finally all the theories proved. Self-motivation and self-awareness variables were determined as predictor variables which can entry into the ultimate regression equation to describe the tendency of employees to accept changes in their electronic education. Manuscript profile
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  3 - An Investigation on the Effect of Multifactor Model of Improving Critical Thinking in E-learning Environments
  mohammadreza nili jamshid heydari hossein moradi
  In the third millennium, people deal with multiple, diverse, and complicated problems as they cannot possess full control over the information, which is constantly produced and accumulated. Having a high skill of critical thinking for assessing the results of different More

  In the third millennium, people deal with multiple, diverse, and complicated problems as they cannot possess full control over the information, which is constantly produced and accumulated. Having a high skill of critical thinking for assessing the results of different issues and decision making about them based on evidences is an unavoidable necessity. The researchers of this work proposed a model with seven factors (components) for critical thinking in e-learning environments. The statistical group of this work is the M.Sc. medical education students of  AZAD university e-learning environments, and the students of the same field from Islamic Azad University traditional education system studying during 2011-2012. Among the research community, 47 members were selected based on a simple random method and divided into two trial (with 23 members) and reference (with 42 members) groups. To train the trial group, the seven-factor critical thinking training scale was utilized in e-learning environments in 15 sessions with empirical sciences course. In the reference group, the same seven-factor critical thinking training scale was used in the classroom environment in lecturing in 15 sessions with empirical sciences course. The model factors and components are challenge, representation, creation of opportunity, creation of motivation, logical analysis, encouragement, responsibility, and commitment. Both groups were subject to two pretest and posttest steps within two trial groups, which were considered as reference to each other. Both groups responded to the Watson- Glaser™ Critical Thinking Appraisal within two pretest and posttest steps, while the covariance analysis statistical test was used for analysis of the results. The results indicate significant difference between the scores between trial and reference groups in improving the critical thinking of the students in terms of inferential, assumption detection, deduction, interpretation, and logical reasoning evaluation components (p=0.001). According to the results, in terms of improving critical thinking, the trial group trained in the e-learning environment indicates higher scores as compared to the group trained in the traditional classroom environment. Manuscript profile